Middle History of Logic Programming: Resolution, Planner, Edinburgh LCF, Prolog, Simula, and the Japanese Fifth Generation Project

Computer Science – Logic in Computer Science

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configurations vs. global states

Scientific paper

Logic Programming can be broadly defined as "using logic to infer computational steps from existing propositions" However, mathematical logic cannot always infer computational steps because computational systems make use of arbitration for determining which message is processed next by a recipient that is sent multiple messages concurrently. Since arrival orders are in general indeterminate, they cannot be inferred from prior information by mathematical logic alone. Therefore mathematical logic cannot in general implement computation. Consequently, Procedural Embedding of Knowledge is strictly more general than Logic Programming. This conclusion is contrary to Robert Kowalski who stated "Looking back on our early discoveries, I value most the discovery that computation could be subsumed by deduction." Nevertheless, logic programming (like functional programming) can be a useful programming idiom. Over the course of history, the term "functional programming" has grown more precise and technical as the field has matured. Logic Programming should be on a similar trajectory. Accordingly, "Logic Programming" should have a general precise characterization. Kowalski's approach has been to advocate limiting Logic Programming to backward-chaining only inference based on resolution using reduction to conjunctive normal form in a global states model. In contrast, our approach is explore Logic Programming building on the logical inference of computational steps using inconsistency-robust reasoning in a configurations model. Because contemporary large software systems are pervasively inconsistent, it is not safe to reason about them using classical logic, e.g., using resolution theorem proving.

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